Strengthening agricultural decisions in countries at risk of food insecurity: The GEOGLAM Crop Monitor for Early Warning

Becker‐Reshef, Inbal; Justice, C. O.; Barker, B.; Humber, M. L.; Rembold, Felix; Bonifácio, Rogério; Zappacosta, Mario; Budde, Mike; Magadzire, Tamuka; Shitote, Chris; Pound, Jonathan; Constantino, Alessandro; Nakalembe, Catherine; Mwangi, Kenneth; Sobue, Shinichi; Newby, Terry; Whitcraft, A. K.; Jarvis, Ian; Verdin, J. P.

doi:10.1016/j.rse.2019.111553

Cited by 80 publications

(66 citation statements)

References 28 publications

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“…Despite the widely acknowledge potential of remote sensing for agricultural monitoring, and the existing EO-derived products, the complexity and variety of African agriculture types (Collier and Dercon, 2014), the complex interactions between weather and geography where diverse rainfall patterns may exist even in nearby areas (Becker-Reshef et al, 2020), and the lack of ancillary data challenge the application of remote sensing approaches that are primarily designed for the global North.…”

Section: The African Agriculture Challenges For Remote Sensingmentioning

confidence: 99%

“…However, since the 1980's weather systems and agricultural statistics systems of several African countries underwent an ongoing decrease of quality, due to a lack of resources and institutional coordination (World Bank et al, 2010). This results in the paucity of ground databases, which is critical for developing and assessing the accuracy of remote sensing based indicators and methods (Becker-Reshef et al, 2020).…”

Section: A Lack Of Ancillary Data With a Limited Accessibilitymentioning

confidence: 99%

“…However, despite the very large improvement in data availability, processing methods, and the stream of dissemination, these systems still suffer from insufficient spatial input data (especially accurate cropland maps, crop calendars, and meteorological data) and methods for better yield predictions (Fritz et al, 2019). However, things are moving forward, and in East Africa, thanks to work with national ministries in Tanzania, Uganda and Kenya, the GEOGLAM Crop Monitor for Early Warning (CM4EW) has recently been adapted for national contexts (Becker-Reshef et al, 2020).…”

Section: Examples Of Current Earth Observation-based Services In Africamentioning

confidence: 99%

See 2 more Smart Citations

Remote Sensing Products and Services in Support of Agricultural Public Policies in Africa: Overview and Challenges

Bégué

Leroux

Soumaré

et al. 2020

Front. Sustain. Food Syst.

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Section: The African Agriculture Challenges For Remote Sensingmentioning

confidence: 99%

Section: A Lack Of Ancillary Data With a Limited Accessibilitymentioning

confidence: 99%

Section: Examples Of Current Earth Observation-based Services In Africamentioning

confidence: 99%

See 1 more Smart Citation

Remote Sensing Products and Services in Support of Agricultural Public Policies in Africa: Overview and Challenges

Bégué

Leroux

Soumaré

et al. 2020

Front. Sustain. Food Syst.

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“…Groundnut farming was studied in this work. Inbal Becker Reshef et al [120], proposed a remote sensing analysis based crop monitoring system for strengthening agricultural decisions and improving crop security. The authors named this model as "GEOGLAM" model which ensures the decision support of all the necessary steps for crop security and analysis.…”

Section: Iot In Crop Monitoringmentioning

confidence: 99%

Recent Developments of the Internet of Things in Agriculture: A Survey

2020

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A rise in the population has immensely increased the pressure on the agriculture sector. With the advent of technology, this decade is witnessing a shift from conventional approaches to the most advanced ones. The Internet of Things (IoT) has transformed both the quality and quantity of the agriculture sector. Hybridization of species along with the real-time monitoring of the farms paved a way for resource optimization. Scientists, research institutions, academicians, and most nations across the globe are moving towards the practice and execution of collaborative projects to explore the horizon of this field for serving mankind. The tech industry is racing to provide more optimal solutions. Inclusion of IoT, along with cloud computing, big data analytics, and wireless sensor networks can provide sufficient scope to predict, process, and analyze the situations and improve the activities in the real-time scenario. The concept of heterogeneity and interoperability of the devices by providing flexible, scalable, and durable methods, models are also opening new domains in this field. Therefore, this paper contributes towards the recent IoT technologies in the agriculture sector, along with the development of hardware and software systems. The public and private sector projects and startup's started all over the globe to provide smart and sustainable solutions in precision agriculture are also discussed. The current scenario, applications, research potential, limitations, and future aspects are briefly discussed. Based on the concepts of IoT a precision farming framework is also proposed in this article.

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“…The speaking plant is the idea of using observed crop processes as the variables to be controlled. The use of internet technology for environmental control in the greenhouse has been used for years [2] as an online monitoring of crop responses as early warning systems to detect and prevent the unintended condition by giving substantial resources needed [3]. Online monitoring system can be used to control the greenhouse environment, such as temperature, humidity, light intensity, and other environmental information using WiFi and it provides a stable, feasible, and low-cost solution for greenhouse production management [4].…”

Section: Introductionmentioning

confidence: 99%

Non-destructive Measurement of Lycopene Content in High Soluble Solids Stored Tomato (Solanum Lycopersicum Mill. cv Rinka 409)

Anggraeni¹,

Khuriyati²,

Falah³

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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High-quality fruits can be produced by controlling the environmental factors, i.e. temperature, relative humidity, carbon dioxide, and light intensity. The tomato (Solanum lycopersicum) variety 'Rinka 409', was grown hydroponically with a high-wire system in high technology greenhouse, Ehime University, Japan. The water stress treatment using visual monitoring system was used to produce the high soluble solids tomato fruits. Moreover, a high lycopene content of tomato can be produced by controlling the storage condition. Non-destructive measurement has been known to provide a fast and accurate quality measurement of fruits and vegetables. The objectives of this study were to develop a precise position for the non-destructive measurement of the lycopene content in high soluble solids stored tomato using Vis/NIR spectroscopy and evaluate its performance. In this study, the high soluble solids of tomato fruits were grown under water stress treatment and stored after harvesting at 25°C in a cool incubator for 7 days. The tomato spectra were measured using Vis/NIR spectroscopy with the wavelength 500-1010 nm. The estimation of the lycopene content was based on the statistical model using multivariate analysis. From this study, it is concluded that the measurement of lycopene content in high soluble solids of tomato fruits after storage by using the top part of the tomato, was better than if it is compared to the side part. It was best determined using PLS analysis with Visible/Near-infrared Spectroscopy non-destructively, with the R 0.98 and RMSE 0.80.

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Strengthening agricultural decisions in countries at risk of food insecurity: The GEOGLAM Crop Monitor for Early Warning

Cited by 80 publications

References 28 publications

Remote Sensing Products and Services in Support of Agricultural Public Policies in Africa: Overview and Challenges

Remote Sensing Products and Services in Support of Agricultural Public Policies in Africa: Overview and Challenges

Recent Developments of the Internet of Things in Agriculture: A Survey

Non-destructive Measurement of Lycopene Content in High Soluble Solids Stored Tomato (Solanum Lycopersicum Mill. cv Rinka 409)

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